Prospective evaluation of periodic breast examination programs: interval cases.

Area of Science:

• Oncology
• Biostatistics
• Public Health

Background:

• Periodic breast cancer screening aims to detect cancers early.
• Interval cancers are diagnosed between scheduled screenings and may have different prognostic characteristics.
• Evaluating the effectiveness of different screening schedules and modalities is crucial for optimizing early detection.

Purpose of the Study:

• To develop mathematical models for estimating breast cancer detection proportions in periodic screening programs.
• To assess the impact of screening schedules and patient self-examinations on interval cancer rates and axillary node metastasis.
• To provide a framework for evaluating the cost-effectiveness of different screening strategies.

Main Methods:

• Development of two mathematical models to estimate expected proportions of breast cancer detection.
• Modeling interval cancer cases and axillary node metastases.
• Evaluation of screening programs with and without patient self-examinations.
• Cost-benefit analysis of mammographic versus physical examinations.

Main Results:

• Reductions in interval cancer cases do not necessarily correlate with equivalent reductions in positive axillary node cases.
• Interval case counts are a relatively weak indicator of a periodic screening program's success.
• Screening programs with lower proportions of interval cases show less dependence on patient self-examinations.
• Cost-benefit analysis suggests physical examinations may be preferred if mammography is significantly more expensive.

Conclusions:

• Interval cancer rates are not a definitive measure of screening program success regarding nodal status.
• Screening program design should consider the trade-offs between different modalities and their costs.
• Mathematical modeling can aid in optimizing periodic breast cancer screening schedules and strategies.